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With rapid improvements and miniaturization in hardware, sensor nodes equipped with acoustic and visual information collection modules promise an unprecedented opportunity for target surveillance applications. This paper investigates a critical task of target surveillance, multi-class classification, in distributed multimedia sensor networks. We first analyze the procedure of target classification utilizing the acoustic and visual information. Then, we propose a binary classification tree based framework for distributed target classification in multimedia sensor networks. The proposed framework includes three main components: Generation of binary classification tree, Division of binary classification tree, and Selection of multimedia sensor nodes. Finally, we conduct an experimental application of target classification and extensive simulations to validate and evaluate our proposed framework and related schemes.